The digitization of the healthcare domain has the potential to drastically improve healthcare services, reduce the time to diagnosis, and lower costs. However, digital applications for the healthcare domain need to be interoperable to maximize their potential. Additionally, with the rapid expansion of Artificial Intelligence (AI) and, specifically, Machine Learning (ML), large amounts of diverse types of data are being utilized. Thus, to achieve interoperability in such applications, the adoption of common semantic data models becomes imperative.

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Colorectal cancer (CRC) is the second leading cause of cancer in Europe, with 1.931.590 people newly diagnosed in 2020. The purpose of this study is the investigation of treatment options and healthcare resource meta-
static CRC (mCRC) in Greece.

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The authors wanted to explore what breast cancer patients want the most from their cancer
treatments. For this purpose, their preferences were collected in four European countries via a discrete
choice experiment. The study showed that patients prefer treatments that improve their ability to function
well in their daily lives and reduce their levels of pain. Patients’ preferences for treatment outcomes might
differ from those of the treating clinicians or regulators. Hence, these aspects can be discussed with their
clinicians to make a joint decision on the choice of treatments.

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Disease Management and Resource Use for the Management of Melanoma stage IIIc or IV Positive for BRAF V600 Mutations in Greece

Objective: Melanoma is one of the most aggressive cancers and is responsible for the majority of skin cancer deaths, with the
presence of metastases prognostic for poor survival. At a time when most cancer incidences are falling, the annual incidence
of melanoma has risen as rapidly as 4-6% in many European countries, with a substantial economic burden in advanced
stages. The objective of this study is the investigation of treatment pathways and healthcare resource use related to advanced
BRAF-mutated melanoma in Greece.

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